Statistical analysis driven optimized deep learning system for intrusion detection

Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology systems. The extent of damage an individual hacker can carry out upon infiltrating a system is well understood. A potentially catastrophic scenario can be envisaged where a nation-state intercepting encrypted financial data gets hacked. Thus, intelligent cybersecurity systems have become inevitably important for improved protection against malicious threats. However, as malware attacks continue to dramatically increase in volume and complexity, it has become ever more challenging for traditional analytic tools to detect and mitigate threat. Furthermore, a huge amount of data produced by large networks has made the recognition task even more complicated and challenging. In this work, we propose an innovative statistical analysis driven optimized deep learning system for intrusion detection. The proposed intrusion detection system (IDS) extracts optimized and more correlated features using big data visualization and statistical analysis methods (human-in-the-loop), followed by a deep autoencoder for potential threat detection. Specifically, a pre-processing module eliminates the outliers and converts categorical variables into one-hot-encoded vectors. The feature extraction module discard features with null values and selects the most significant features as input to the deep autoencoder model (trained in a greedy-wise manner). The NSL-KDD dataset from the Canadian Institute for Cybersecurity is used as a benchmark to evaluate the feasibility and effectiveness of the proposed architecture. Simulation results demonstrate the potential of our proposed system and its outperformance as compared to existing state-of-the-art methods and recently published novel approaches. Ongoing work includes further optimization and real-time evaluation of our proposed IDS.Comment: To appear in the 9th International Conference on Brain Inspired Cognitive Systems (BICS 2018

Hydrostatic pressure does not cause detectable changes to survival of human retinal ganglion

Purpose: Elevated intraocular pressure (IOP) is a major risk factor for glaucoma. One consequence of raised IOP is that ocular tissues are subjected to increased hydrostatic pressure (HP). The effect of raised HP on stress pathway signaling and retinal ganglion cell (RGC) survival in the human retina was investigated. Methods: A chamber was designed to expose cells to increased HP (constant and fluctuating). Accurate pressure control (10-100mmHg) was achieved using mass flow controllers. Human organotypic retinal cultures (HORCs) from donor eyes (<24h post mortem) were cultured in serum-free DMEM/HamF12. Increased HP was compared to simulated ischemia (oxygen glucose deprivation, OGD). Cell death and apoptosis were measured by LDH and TUNEL assays, RGC marker expression by qRT-PCR (THY-1) and RGC number by immunohistochemistry (NeuN). Activated p38 and JNK were detected by Western blot. Results: Exposure of HORCs to constant (60mmHg) or fluctuating (10-100mmHg; 1 cycle/min) pressure for 24 or 48h caused no loss of structural integrity, LDH release, decrease in RGC marker expression (THY-1) or loss of RGCs compared with controls. In addition, there was no increase in TUNEL-positive NeuN-labelled cells at either time-point indicating no increase in apoptosis of RGCs. OGD increased apoptosis, reduced RGC marker expression and RGC number and caused elevated LDH release at 24h. p38 and JNK phosphorylation remained unchanged in HORCs exposed to fluctuating pressure (10-100mmHg; 1 cycle/min) for 15, 30, 60 and 90min durations, whereas OGD (3h) increased activation of p38 and JNK, remaining elevated for 90min post-OGD. Conclusions: Directly applied HP had no detectable impact on RGC survival and stress-signalling in HORCs. Simulated ischemia, however, activated stress pathways and caused RGC death. These results show that direct HP does not cause degeneration of RGCs in the ex vivo human retina

Coupled coarse graining and Markov Chain Monte Carlo for lattice systems

We propose an efficient Markov Chain Monte Carlo method for sampling equilibrium distributions for stochastic lattice models, capable of handling correctly long and short-range particle interactions. The proposed method is a Metropolis-type algorithm with the proposal probability transition matrix based on the coarse-grained approximating measures introduced in a series of works of M. Katsoulakis, A. Majda, D. Vlachos and P. Plechac, L. Rey-Bellet and D.Tsagkarogiannis,. We prove that the proposed algorithm reduces the computational cost due to energy differences and has comparable mixing properties with the classical microscopic Metropolis algorithm, controlled by the level of coarsening and reconstruction procedure. The properties and effectiveness of the algorithm are demonstrated with an exactly solvable example of a one dimensional Ising-type model, comparing efficiency of the single spin-flip Metropolis dynamics and the proposed coupled Metropolis algorithm.Comment: 20 pages, 4 figure

The Formation of the First Low-Mass Stars From Gas With Low Carbon and Oxygen Abundances

The first stars in the Universe are predicted to have been much more massive than the Sun. Gravitational condensation accompanied by cooling of the primordial gas due to molecular hydrogen, yields a minimum fragmentation scale of a few hundred solar masses. Numerical simulations indicate that once a gas clump acquires this mass, it undergoes a slow, quasi-hydrostatic contraction without further fragmentation. Here we show that as soon as the primordial gas - left over from the Big Bang - is enriched by supernovae to a carbon or oxygen abundance as small as ~0.01-0.1% of that found in the Sun, cooling by singly-ionized carbon or neutral oxygen can lead to the formation of low-mass stars. This mechanism naturally accommodates the discovery of solar mass stars with unusually low (10^{-5.3} of the solar value) iron abundance but with a high (10^{-1.3} solar) carbon abundance. The minimum stellar mass at early epochs is partially regulated by the temperature of the cosmic microwave background. The derived critical abundances can be used to identify those metal-poor stars in our Milky Way galaxy with elemental patterns imprinted by the first supernovae.Comment: 14 pages, 2 figures (appeared today in Nature

Monodromy--like Relations for Finite Loop Amplitudes

We investigate the existence of relations for finite one-loop amplitudes in Yang-Mills theory. Using a diagrammatic formalism and a remarkable connection between tree and loop level, we deduce sequences of amplitude relations for any number of external legs.Comment: 24 pages, 6 figures, v2 typos corrected, reference adde

High Effective Coverage of Vector Control Interventions in Children After Achieving Low Malaria Transmission in Zanzibar, Tanzania.

\ud \ud Formerly a high malaria transmission area, Zanzibar is now targeting malaria elimination. A major challenge is to avoid resurgence of malaria, the success of which includes maintaining high effective coverage of vector control interventions such as bed nets and indoor residual spraying (IRS). In this study, caretakers' continued use of preventive measures for their children is evaluated, following a sharp reduction in malaria transmission. A cross-sectional community-based survey was conducted in June 2009 in North A and Micheweni districts in Zanzibar. Households were randomly selected using two-stage cluster sampling. Interviews were conducted with 560 caretakers of under-five-year old children, who were asked about perceptions on the malaria situation, vector control, household assets, and intention for continued use of vector control as malaria burden further decreases. Effective coverage of vector control interventions for under-five children remains high, although most caretakers (65%; 363/560) did not perceive malaria as presently being a major health issue. Seventy percent (447/643) of the under-five children slept under a long-lasting insecticidal net (LLIN) and 94% (607/643) were living in houses targeted with IRS. In total, 98% (628/643) of the children were covered by at least one of the vector control interventions. Seasonal bed-net use for children was reported by 25% (125/508) of caretakers of children who used bed nets. A high proportion of caretakers (95%; 500/524) stated that they intended to continue using preventive measures for their under-five children as malaria burden further reduces. Malaria risk perceptions and different perceptions of vector control were not found to be significantly associated with LLIN effective coverage While the majority of caretakers felt that malaria had been reduced in Zanzibar, effective coverage of vector control interventions remained high. Caretakers appreciated the interventions and recognized the value of sustaining their use. Thus, sustaining high effective coverage of vector control interventions, which is crucial for reaching malaria elimination in Zanzibar, can be achieved by maintaining effective delivery of these interventions

Emotional Fuzzy Sliding-Mode Control for Unknown Nonlinear Systems

[[abstract]]The brain emotional learning model can be implemented with a simple hardware and processor; however, the learning model cannot model the qualitative aspects of human knowledge. To solve this problem, a fuzzy-based emotional learning model (FELM) with structure and parameter learning is proposed. The membership functions and fuzzy rules can be learned through the derived learning scheme. Further, an emotional fuzzy sliding-mode control (EFSMC) system, which does not need the plant model, is proposed for unknown nonlinear systems. The EFSMC system is applied to an inverted pendulum and a chaotic synchronization. The simulation results with the use of EFSMC system demonstrate the feasibility of FELM learning procedure. The main contributions of this paper are (1) the FELM varies its structure dynamically with a simple computation; (2) the parameter learning imitates the role of emotions in mammalians brain; (3) by combining the advantage of nonsingular terminal sliding-mode control, the EFSMC system provides very high precision and finite-time control performance; (4) the system analysis is given in the sense of the gradient descent method.[[notice]]補正完

Automated detection of congenital heart disease in fetal ultrasound screening

Prenatal screening with ultrasound can lower neonatal mortality significantly for selected cardiac abnormalities. However, the need for human expertise, coupled with the high volume of screening cases, limits the practically achievable detection rates. In this paper we discuss the potential for deep learning techniques to aid in the detection of congenital heart disease (CHD) in fetal ultrasound. We propose a pipeline for automated data curation and classification. During both training and inference, we exploit an auxiliary view classification task to bias features toward relevant cardiac structures. This bias helps to improve in F1-scores from 0.72 and 0.77 to 0.87 and 0.85 for healthy and CHD classes respectively

Fluctuations of a holographic quantum Hall fluid

We analyze the neutral spectrum of the holographic quantum Hall fluid described by the D2-D8' model. As expected for a quantum Hall state, we find the system to be stable and gapped and that, at least over much of the parameter space, the lowest excitation mode is a magneto-roton. In addition, we find magneto-rotons in higher modes as well. We show that these magneto-rotons are direct consequences of level crossings between vector and scalar modes.Comment: 20 pages, 8 figures; v.2 figures improved, 2 figures added, and text clarified particularly in Sec. 5, to appear in JHE

Expansion of anti-AFP Th1 and Tc1 responses in hepatocellular carcinoma occur in different stages of disease

Copyright @ 2010 Cancer Research UK. This work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/.Background: α-Fetoprotein (AFP) is a tumour-associated antigen in hepatocellular carcinoma (HCC) and is a target for immunotherapy. However, there is little information on the pattern of CD4 (Th1) and CD8 (Tc1) T-cell response to AFP in patients with HCC and their association with the clinical characteristics of patients. Methods: We therefore analysed CD4 and CD8 T-cell responses to a panel of AFP-derived peptides in a total of 31 HCC patients and 14 controls, using an intracellular cytokine assay for IFN-γ. Results: Anti-AFP Tc1 responses were detected in 28.5% of controls, as well as in 25% of HCC patients with Okuda I (early tumour stage) and in 31.6% of HCC patients with stage II or III (late tumour stages). An anti-AFP Th1 response was detected only in HCC patients (58.3% with Okuda stage I tumours and 15.8% with Okuda stage II or III tumours). Anti-AFP Th1 response was mainly detected in HCC patients who had normal or mildly elevated serum AFP concentrations (P=0.00188), whereas there was no significant difference between serum AFP concentrations in these patients and the presence of an anti-AFP Tc1 response. A Th1 response was detected in 44% of HCC patients with a Child–Pugh A score (early stage of cirrhosis), whereas this was detected in only 15% with a B or C score (late-stage cirrhosis). In contrast, a Tc1 response was detected in 17% of HCC patients with a Child–Pugh A score and in 46% with a B or C score. Conclusion: These results suggest that anti-AFP Th1 responses are more likely to be present in patients who are in an early stage of disease (for both tumour stage and liver cirrhosis), whereas anti-AFP Tc1 responses are more likely to be present in patients with late-stage liver cirrhosis. Therefore, these data provide valuable information for the design of vaccination strategies against HCC.Association for International Cancer Research and Polkemmet Fund, London Clinic